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Record W7057758985

Introduzione a "La luce e l'inchiostro"...

2019· book-chapter· it· W7057758985 on OpenAlexaboutno aff

Bibliographic record

VenueCINECA IRIS Institutial research information system (University of Pisa) · 2019
Typebook-chapter
Languageit
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsLingua francaSocial lifeConjunction (astronomy)
DOInot available

Abstract

fetched live from OpenAlex

L'introduzione riflette sulla raccolta di saggi che indagano, da diverse prospettive, l’interazione tra l’arte della parola umana, la letteratura, e la fotografia, una forma relativamente recente di rappresentazione visiva della realtà spesso dotata di pieno valore artistico. Confermando conclusioni teorico-metodologiche già delineate da fondamentali interventi critici in materia, i contributi provano a gettare luce su zone ancora in ombra di un ambito del sapere per sua natura multidisciplinare e dunque sfuggente. \nI saggi qui riuniti ripercorrono tutto l’arco cronologico del rapporto tra testo letterario e immagine fotografica, dando ragione dell’intera durata di un dialogo che si è instaurato a partire dalle origini ottocentesche della fotografia ed è rimasto vivacissimo e produttivo sino al presente. Essendo tutti focalizzati su opere scritte in lingua inglese, questi interventi finiscono ineluttabilmente per tracciare una piccola storia della letteratura anglofona successiva al Romanticismo (e dunque, per molti aspetti, contemporanea). Muovendosi tra l’epoca vittoriana e l’Ipermodernità, tra il Regno Unito, gli Stati Uniti e il Canada, il volume si propone di rileggere momenti ed esperienze chiave della tradizione letteraria di lingua inglese attraverso l’ottica privilegiata dei suo contatti col medium fotografico.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.035
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0060.008
Scholarly communication0.0080.006
Open science0.0010.004
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0350.014

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.264
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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